As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal probability distribution whenever the sample size is large.
<h3>What is the Central limit theorem?</h3>
- The Central limit theorem says that the normal probability distribution is used to approximate the sampling distribution of the sample proportions and sample means whenever the sample size is large.
- Approximation of the distribution occurs when the sample size is greater than or equal to 30 and n(1 - p) ≥ 5.
Thus, as a rule of thumb, the sampling distribution of the sample proportions can be approximated by a normal probability distribution when the sample size is large and each element is selected independently from the same population.
Learn more about the central limit theorem here:
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Hello,
1.8444444....=1.8+1/10*0.44444....
=1.8+1/10*4/9
=1.8+4/90
=162/90+4/90
=166/90
=83/45
2.126262626...=2.1+1/10*0.262626...
=2.1+1/10*26/99
=2.1+26/990
=2079/990+26/990
=2105/990
=421/198
The answer would be -161z-3a
Answer: d
Step-by-step explanation:
y is the price of the ticket x is the number sold
Answer:
x=0
Step-by-step explanation:
7x+(-7)=9x-7
Add 7 to each side
7x+(-7)7=9x-7+7
7x = 9x
Subtract 7x from each side
7x-7x = 9x-7x
0 = 2x
Divide by 2
0 = 2x/2
0 = x